FFmpeg
dnn_backend_native_layer_dense.c
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1 /*
2  * Copyright (c) 2020
3  *
4  * This file is part of FFmpeg.
5  *
6  * FFmpeg is free software; you can redistribute it and/or
7  * modify it under the terms of the GNU Lesser General Public
8  * License as published by the Free Software Foundation; either
9  * version 2.1 of the License, or (at your option) any later version.
10  *
11  * FFmpeg is distributed in the hope that it will be useful,
12  * but WITHOUT ANY WARRANTY; without even the implied warranty of
13  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
14  * Lesser General Public License for more details.
15  *
16  * You should have received a copy of the GNU Lesser General Public
17  * License along with FFmpeg; if not, write to the Free Software
18  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
19  */
20 
21 #include "libavutil/avassert.h"
23 
24 int ff_dnn_load_layer_dense(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
25 {
26  DenseParams *dense_params;
27  int kernel_size;
28  int dnn_size = 0;
29  dense_params = av_malloc(sizeof(*dense_params));
30  if (!dense_params)
31  return 0;
32 
33  dense_params->activation = (int32_t)avio_rl32(model_file_context);
34  dense_params->input_num = (int32_t)avio_rl32(model_file_context);
35  dense_params->output_num = (int32_t)avio_rl32(model_file_context);
36  dense_params->has_bias = (int32_t)avio_rl32(model_file_context);
37  dnn_size += 16;
38 
39  kernel_size = dense_params->input_num * dense_params->output_num;
40  dnn_size += kernel_size * 4;
41  if (dense_params->has_bias)
42  dnn_size += dense_params->output_num * 4;
43 
44  if (dnn_size > file_size || dense_params->input_num <= 0 ||
45  dense_params->output_num <= 0){
46  av_freep(&dense_params);
47  return 0;
48  }
49 
50  dense_params->kernel = av_malloc(kernel_size * sizeof(float));
51  if (!dense_params->kernel) {
52  av_freep(&dense_params);
53  return 0;
54  }
55  for (int i = 0; i < kernel_size; ++i) {
56  dense_params->kernel[i] = av_int2float(avio_rl32(model_file_context));
57  }
58 
59  dense_params->biases = NULL;
60  if (dense_params->has_bias) {
61  dense_params->biases = av_malloc(dense_params->output_num * sizeof(float));
62  if (!dense_params->biases){
63  av_freep(&dense_params->kernel);
64  av_freep(&dense_params);
65  return 0;
66  }
67  for (int i = 0; i < dense_params->output_num; ++i){
68  dense_params->biases[i] = av_int2float(avio_rl32(model_file_context));
69  }
70  }
71 
72  layer->params = dense_params;
73 
74  layer->input_operand_indexes[0] = (int32_t)avio_rl32(model_file_context);
75  layer->output_operand_index = (int32_t)avio_rl32(model_file_context);
76  dnn_size += 8;
77 
78  if (layer->input_operand_indexes[0] >= operands_num || layer->output_operand_index >= operands_num) {
79  return 0;
80  }
81 
82  return dnn_size;
83 }
84 
85 int ff_dnn_execute_layer_dense(DnnOperand *operands, const int32_t *input_operand_indexes,
86  int32_t output_operand_index, const void *parameters, NativeContext *ctx)
87 {
88  float *output;
89  int32_t input_operand_index = input_operand_indexes[0];
90  int number = operands[input_operand_index].dims[0];
91  int height = operands[input_operand_index].dims[1];
92  int width = operands[input_operand_index].dims[2];
93  int channel = operands[input_operand_index].dims[3];
94  const float *input = operands[input_operand_index].data;
95  const DenseParams *dense_params = parameters;
96 
97  int src_linesize = width * channel;
98  DnnOperand *output_operand = &operands[output_operand_index];
99  output_operand->dims[0] = number;
100  output_operand->dims[1] = height;
101  output_operand->dims[2] = width;
102  output_operand->dims[3] = dense_params->output_num;
103  output_operand->data_type = operands[input_operand_index].data_type;
104  output_operand->length = ff_calculate_operand_data_length(output_operand);
105  if (output_operand->length <= 0) {
106  av_log(ctx, AV_LOG_ERROR, "The output data length overflow\n");
107  return DNN_ERROR;
108  }
109  output_operand->data = av_realloc(output_operand->data, output_operand->length);
110  if (!output_operand->data) {
111  av_log(ctx, AV_LOG_ERROR, "Failed to reallocate memory for output\n");
112  return DNN_ERROR;
113  }
114  output = output_operand->data;
115 
116  av_assert0(channel == dense_params->input_num);
117 
118  for (int y = 0; y < height; ++y) {
119  for (int x = 0; x < width; ++x) {
120  for (int n_filter = 0; n_filter < dense_params->output_num; ++n_filter) {
121  if (dense_params->has_bias)
122  output[n_filter] = dense_params->biases[n_filter];
123  else
124  output[n_filter] = 0.f;
125 
126  for (int ch = 0; ch < dense_params->input_num; ++ch) {
127  float input_pel;
128  input_pel = input[y * src_linesize + x * dense_params->input_num + ch];
129  output[n_filter] += input_pel * dense_params->kernel[n_filter*dense_params->input_num + ch];
130  }
131  switch (dense_params->activation){
132  case RELU:
133  output[n_filter] = FFMAX(output[n_filter], 0.0);
134  break;
135  case TANH:
136  output[n_filter] = 2.0f / (1.0f + exp(-2.0f * output[n_filter])) - 1.0f;
137  break;
138  case SIGMOID:
139  output[n_filter] = 1.0f / (1.0f + exp(-output[n_filter]));
140  break;
141  case NONE:
142  break;
143  case LEAKY_RELU:
144  output[n_filter] = FFMAX(output[n_filter], 0.0) + 0.2 * FFMIN(output[n_filter], 0.0);
145  }
146  }
147  output += dense_params->output_num;
148  }
149  }
150  return 0;
151 }
NONE
@ NONE
Definition: af_afade.c:54
ff_dnn_load_layer_dense
int ff_dnn_load_layer_dense(Layer *layer, AVIOContext *model_file_context, int file_size, int operands_num)
Definition: dnn_backend_native_layer_dense.c:24
output
filter_frame For filters that do not use the this method is called when a frame is pushed to the filter s input It can be called at any time except in a reentrant way If the input frame is enough to produce output
Definition: filter_design.txt:225
ff_dnn_execute_layer_dense
int ff_dnn_execute_layer_dense(DnnOperand *operands, const int32_t *input_operand_indexes, int32_t output_operand_index, const void *parameters, NativeContext *ctx)
Definition: dnn_backend_native_layer_dense.c:85
av_malloc
#define av_malloc(s)
Definition: tableprint_vlc.h:31
av_int2float
static av_always_inline float av_int2float(uint32_t i)
Reinterpret a 32-bit integer as a float.
Definition: intfloat.h:40
ff_calculate_operand_data_length
int32_t ff_calculate_operand_data_length(const DnnOperand *oprd)
Definition: dnn_backend_native.c:403
SIGMOID
@ SIGMOID
Definition: dnn_backend_native.h:54
avassert.h
AV_LOG_ERROR
#define AV_LOG_ERROR
Something went wrong and cannot losslessly be recovered.
Definition: log.h:194
width
#define width
TANH
@ TANH
Definition: dnn_backend_native.h:54
DnnOperand::data
void * data
data pointer with data length in bytes.
Definition: dnn_backend_native.h:103
av_assert0
#define av_assert0(cond)
assert() equivalent, that is always enabled.
Definition: avassert.h:37
DnnOperand::data_type
DNNDataType data_type
support different kinds of data type such as float, half float, int8 etc, first support float now.
Definition: dnn_backend_native.h:84
DenseParams::biases
float * biases
Definition: dnn_backend_native_layer_dense.h:31
ctx
AVFormatContext * ctx
Definition: movenc.c:48
f
#define f(width, name)
Definition: cbs_vp9.c:255
int32_t
int32_t
Definition: audio_convert.c:194
Layer::params
void * params
Definition: dnn_backend_native.h:65
NULL
#define NULL
Definition: coverity.c:32
DenseParams::activation
DNNActivationFunc activation
Definition: dnn_backend_native_layer_dense.h:28
DnnOperand::dims
int32_t dims[4]
there are two memory layouts, NHWC or NCHW, so we use dims, dims[0] is Number.
Definition: dnn_backend_native.h:73
exp
int8_t exp
Definition: eval.c:72
DnnOperand::length
int32_t length
Definition: dnn_backend_native.h:104
avio_rl32
unsigned int avio_rl32(AVIOContext *s)
Definition: aviobuf.c:750
AVIOContext
Bytestream IO Context.
Definition: avio.h:161
Layer::output_operand_index
int32_t output_operand_index
Definition: dnn_backend_native.h:64
NativeContext
Definition: dnn_backend_native.h:116
Layer
Definition: dnn_backend_native.h:56
Layer::input_operand_indexes
int32_t input_operand_indexes[4]
a layer can have multiple inputs and one output.
Definition: dnn_backend_native.h:63
FFMAX
#define FFMAX(a, b)
Definition: common.h:103
DenseParams::input_num
int32_t input_num
Definition: dnn_backend_native_layer_dense.h:27
height
#define height
FFMIN
#define FFMIN(a, b)
Definition: common.h:105
input
and forward the test the status of outputs and forward it to the corresponding return FFERROR_NOT_READY If the filters stores internally one or a few frame for some input
Definition: filter_design.txt:172
RELU
@ RELU
Definition: dnn_backend_native.h:54
av_realloc
void * av_realloc(void *ptr, size_t size)
Allocate, reallocate, or free a block of memory.
Definition: mem.c:134
i
int i
Definition: input.c:407
DenseParams
Definition: dnn_backend_native_layer_dense.h:26
DenseParams::kernel
float * kernel
Definition: dnn_backend_native_layer_dense.h:30
DNN_ERROR
@ DNN_ERROR
Definition: dnn_interface.h:33
DenseParams::output_num
int32_t output_num
Definition: dnn_backend_native_layer_dense.h:27
DnnOperand
Definition: dnn_backend_native.h:68
dnn_backend_native_layer_dense.h
LEAKY_RELU
@ LEAKY_RELU
Definition: dnn_backend_native.h:54
av_freep
#define av_freep(p)
Definition: tableprint_vlc.h:35
av_log
#define av_log(a,...)
Definition: tableprint_vlc.h:28
channel
channel
Definition: ebur128.h:39
DenseParams::has_bias
int32_t has_bias
Definition: dnn_backend_native_layer_dense.h:29